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LitCovid-AGAC: cellular and molecular level annotation data set based on COVID-19

Currently, coronavirus disease 2019 (COVID-19) literature has been increasing dramatically, and the increased text amount make it possible to perform large scale text mining and knowledge discovery. Therefore, curation of these texts becomes a crucial issue for Bio-medical Natural Language Processin...

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Detalles Bibliográficos
Autores principales:	Ouyang, Sizhuo, Wang, Yuxing, Zhou, Kaiyin, Xia, Jingbo
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Korea Genome Organization 2021
Materias:	Blah7
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8510875/ https://www.ncbi.nlm.nih.gov/pubmed/34638170 http://dx.doi.org/10.5808/gi.21013

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